Accelerating Value Delivery: Mastering Speed Metrics like Cycle Time & Lead Time to Value

Metrics Masterclass: Accelerating Value Delivery with Speed Metrics

Join us for the next session in Plandek’s Masterclass series, where we spotlight Speed – one of the Four Pillars of Software Engineering Productivity.

In this session, we’ll explore how engineering teams can not only increase delivery speed – but also accelerate the flow of value to customers. Using Plandek’s engineering productivity metrics, you’ll learn how to reduce waste in software delivery, optimize Cycle Time, and unlock quicker feedback loops, all while maintaining quality and control.

In this session, you’ll learn how to:

• Understand and take action on key Speed metrics in DevOps, including:

  • Lead Time to Value

  • Cycle Time

  • Time to Merge PRs

  • Time to Deploy

  • Merge Frequency per Author

  • Identify where time is lost across your SDLC and what to do about it

• Set practical targets using Plandek’s 2025 Benchmarks, including what “top quartile” Cycle Time performance looks like

• Shorten delivery timelines by fixing inefficiencies in PR and deployment workflows

• Use Speed insights to drive cross-team collaboration and product-market responsiveness

Bonus highlight: Discover how Plandek’s SmartView surfaces hidden blockers in real time – so your teams can fix issues before they delay delivery. You’ll see how SmartView helps reduce Cycle Time by giving teams and leaders a live window into work in progress.

And critically… We’ll examine how speed supports engineering morale, autonomy, and customer impact – because speed isn’t just about going fast; it’s about empowering teams to deliver with clarity and confidence.

Measure the real impact of GenAI tools like GitHub Copilot

As GenAI tools like GitHub Copilot become embedded in modern development workflows, it’s critical to separate hype from measurable impact.

This session will show you how to assess GenAI’s real contribution to delivery performance using key Speed metrics:

• Determine if Cycle Time and Time to Merge are improving in parallel with Copilot adoption

• Measure increases in Merge Frequency per Author to evaluate whether developers are shipping code in smaller, faster increments

• Track Lead Time to Value to understand if GenAI accelerates delivery from idea to production

• Identify where GenAI adoption isn’t moving the dial – so you can target deeper workflow improvements

• Gain the insight needed to make informed decisions about GenAI investment and its role in your engineering strategy.